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Record W2917731977 · doi:10.3390/cells8030202

Aquaporins Respond to Chilling in the Phloem by Altering Protein and mRNA Expression

2019· article· en· W2917731977 on OpenAlexaff
Ryan C. Stanfield, Joan Laur

Bibliographic record

VenueCells · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsUniversité de MontréalUniversity of Alberta
Fundersnot available
KeywordsPhloemSieve tube elementAquaporinCell biologyPlasmodesmaBiologyMessenger RNAWater transportBotanyBiophysicsChemistryCytoplasmWater flowBiochemistryGene

Abstract

fetched live from OpenAlex

Previous experiments using heat exchangers (liquid cooled blocks) to chill a portion of plant stem have shown a transient stoppage in phloem translocation and an increase in measured phloem pressure. Although a chilled-induced stoppage of phloem transport has been known for over 100 years, the mechanism of this phenomenon is still poorly understood. Recently, work has highlighted that aquaporins occur within the plasma membrane of the sieve tubes along the entire source-to-sink pathway, and that isoforms of these water channel proteins may change dynamically. Aquaporins show regulatory roles in controlling tissue and cellular water status in response to environmental hardships. Thus, we tested if protein localization and mRNA transcript abundance changes occur in response to chilling in balsam poplar (Populus balsamifera) using immunohistochemistry and qrtPCR. The results of the immunolocalization experiments show that the labeling intensity of the sieve elements treated for only 2 min of chill time significantly increased for PIP2. After 10 min of chilling, this signal declined significantly to lower than that of the pre-chilled sieve elements. Overall, the abundance of mRNA transcript increased for the tested PIP2s following cold application. We discuss the implication that aquaporins are responsible for the alleviation of sieve tube pressure and the resumption of flow following a cold-induced blockage event.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score0.081

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.190
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2019
Admission routes1
Has abstractyes

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